Abstract
A number of educational researchers have developed pedagogical approaches that involve the teacher in discovering and helping to correct misconceptions that students bring to their study of their subject matter. During the last decade, several computer systems have been developed to support teaching and learning using this kind of approach. A central conceptual construct used by these systems is the "facet" of understanding: an atomic diagnosable unit of belief. A formidable challenge to applying such pedagogical approaches to new topic areas is the task of discovering and organizing the facets for the new subject area. This paper presents a taxonomy of misconceptions and a methodology for going about the task of preparing a database of facets. Important issues include the generality and diagnosability of facets, granularity of facets, and their placement on a scale of problematicity. Examples are drawn from the subjects of physics and computer science and in the context of two computer systems: the Diagnoser and INFACT. <strong>Editors: </strong>Patrick McAndrew (Open University, UK). <strong>Reviewers:</strong> Paul Horwitz (Concord Consortium, USA) and Ruth Thomas (Jelsim Partnership, UK).
Highlights
1.1 MotivationStudents do not come to the classroom as blank slates; they have prior knowledge
The fourth type of proto-facet is used to capture both a conception or misconception and actual evidence for it. (“I think heavier objects always fall faster than lighter objects.”) A small amount of generalization can be performed by the designer so that the proto-facet handles some alternative expressions of the same idea. (e.g., “[heavier | bigger] [objects | things] fall [faster | quicker | more quickly] than [lighter | smaller] [objects | things | ones]”)
“problematicity” may take on a new meaning: how hard is it to move a student from their deeplyheld misconception to a more correct understanding? Regardless of the expertise level associated with such facets, the learning and instruction required to overcome them is disproportionate to their proximity to expert understanding
Summary
Students do not come to the classroom as blank slates; they have prior knowledge. Because learning involves transferring this knowledge to new situations, prior knowledge can make it difficult to learn new things. Even if identification of student prior knowledge is not the most efficient way to help a student to learn from a cognitive perspective, it may have a huge impact on student engagement. A student who is excited by discussing his or her ideas may become more motivated to learn. This creates a need to identify student preconceptions and use them to guide classroom activities. Such a strategy is one way to perform and use formative assessment, which has been shown by many, such.
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